1. No category

WZB-Postprints
Jianghong Li, Sarah E. Johnson, Wen-Jui Han, Sonia Andrews, Garth Kendall,
Lyndall Strazdins, Alfred Dockery
Parents‘ Nonstandard Work Schedules and Child Wellbeing
A Critical Review of the Literature
Suggested citation:
Li, Jianghong/Johnson, Sarah E./Han, Wen-Jui/Andrews, Sonia/Kendall, Garth/Strazdins,
Lyndall/Dockery, Alfred (2013): Parents‘ Nonstandard Work Schedules and Child
Wellbeing. A Critical Review of the Literature, online:
http://www.wzb.eu/sites/default/files/publikationen/postprints/li_parents_nonstandar
d_work_schedules_and_child_wellbeing.pdf
The article has been published online first in The Journal of Primary Prevention:
http://dx.doi.org/10.1007/s10935-013-0318-z.
Parents' nonstandard work schedules and child wellbeing: A critical review of the literature
Jianghong Liabc, Sarah E Johnsonab, Wen-Jui Hand, Sonia Andrewse, Garth Kendallbf, Lyndall
Strazdinsg and Alfred Dockerl
aCurtin Health Innovation Research Institute, Centre for Population Health Research, Curtin
University, PO Box 855, West Perth, Western Australia, 6872, Australia.
bTelethon Institute for Child Health Research, Centre for Child Health Research, The
University ofWestern Australia, Perth, Australia.
cWZB Berlin Social Research Center, Reichpietschufer 50, 10785 Berlin, Germany.
dSilver School of Social Work, New York University, 1 Washington Square North, New
York, NY 10003.
eCurtin Business School, Curtin University, GPO Box U1987, Perth, Western Australia,
6845, Australia.
fSchool of Nursing and Midwifery, Curtin Health Innovation Research Institute, Curtin
University, GPO Box U1987, Perth, Western Australia, 6845, Australia.
gNational Centre for Epidemiology and Population Health, College of Medicine, Biology &
Environment, Building 62, M Block, The Australian National University, ACT, Australia.
Corresponding author: Jianghong Li
Senior Researcher
WZB Berlin Social Research Center
(Wissenschaftszentmm Berlin fur Sozialforschung g GmbH: www.wzb.eu)
Reichpietschufer 50
10785 Berlin, Germany
Tel: +49 30 254 91 564
Fax: +49 30 254 91 562
Email: j ianghong.li@wzb. eu
1
Parents' nonstandard work schedules and child well-being: A critical review of the
literature
2
ABSTRACT
This paper provides a comprehensive review of empirical evidence linking parental
nonstandard work schedules to four main child developmental outcomes: internalizing and
externalizing problems, cognitive development, and body mass index. We evaluated the
studies based on theory and methodological rigor (longitudinal data, representative samples,
consideration of selection and information bias, confounders, moderators, and mediators). Of
23 studies published between 1980 and 2012 that met the selection criteria, 21 reported
significant associations between nonstandard work schedules and an adverse child
developmental outcome. The associations were partially mediated through parental
depressive symptoms, low quality parenting, reduced child-parent interaction and closeness,
and a less supportive home environment. These associations were more pronounced in
disadvantaged families and when parents worked such schedules full time. We discuss the
nuance, strengths, and limitations of the existing studies, and propose recommendations for
future research.
Keywords: Child mental health, Child obesity, Cognitive development, Nonstandard work
schedules, Parental employment, Shift work
3
INTRODUCTION
Around the world, many societies are transitioning from industrial and post-industrial
economies to service economies, which Presser (2003, pp. 64-65) calls the "24/7 economy."
Accompanying this economy is a demand for services around the clock, which has driven a
rise in work schedules in evenings, nights, and weekends (so called "nonstandard
schedules"). Research to date has documented a high prevalence of nonstandard (NS) work
schedules in developed economies (ABS, 2009; McMenamin, 2007; Presser, 2003; Presser,
Gornick, & Parashar, 2008; Williams, 2008), particularly among parents (ABS, 2009;
Presser, 2003). This labor market trend has raised concerns about its potential impact on
children's well-being.
The influence ofNS work schedules on children's health and development is an
important issue for social, economic and workplace policy. Future economic prosperity and
social cohesion are contingent on all children having optimal physical and mental health and
the capacity to participate fully in the workplace and society. If there were convincing
evidence that children's health and development is adversely influenced by parents' work
schedules, it would strengthen the case for improving work conditions and for family friendly
workplace reform. Such evidence would also make a strong argument for appropriate income
support and child care provision for families with children.
The purpose of this paper is to provide a critical review and assessment of the
evidence for the influence of parents' NS work schedules on their children's well-being. We
confine the review to research on developed countries, discuss policy implications of the
evidence, and offer directions for future research in this field.
Definition and Prevalence ofNS Work Schedules
4
The definition ofNS work schedules varies across studies and countries, but essentially refers
to schedules in which the majority of work hours fall outside a typical daytime Monday to
Friday work week. In general, NS schedules include evenings, nights, rotating shifts (i.e.,
alternating between day, evening, or night shifts, but on a fixed schedule), split shifts,
irregular hours, and regular weekend work.
Based on United States (US) data from the Work Schedules and Work at Home
Survey a supplement to the Current Population Survey in 2004, about 18% of all employed
wage and salary workers ( 19% of men and 16% of women) reported a work shift for their
primary job that fell outside of a usual daytime schedule (between 6am and 6pm)
(McMenamin, 2007). The prevalence ofNS work schedules is much higher among African
Americans (23%), part-time workers (29%), and workers employed in the service sector
(36%) (McMenamin, 2007). NS work schedules are also prevalent in other developed
economies but, due to different definitions, their prevalence may not be directly compared
across countries. In 2005, about 28% of Canadian workers worked a NS schedule, the vast
majority of whom were full-time shift workers (Williams, 2008). Between 2001 and 2004,
about 43% of Australian workers regularly worked some form ofNS schedule, including
weekends (Dockery, Li, & Kendall, 2009). Within Europe, the prevalence of weekday shift
work varied widely across countries during 2005, from 15% in Luxembourg to 30% in the
United Kingdom. The prevalence of usual weekend shift work ranged from 10% in Sweden
to 34% in Italy (Presser et al., 2008).
Parents with young children tend to be more likely to work NS schedules due to child
care needs or costs, or because parents wish to maximize their time with children while
undertaking the employment by 'shift' or 'tag-team' parenting (Barnett & Gareis, 2007;
Garey, 1999; Han, 2004; Hattery, 2001; Presser, 2003; Wight, Raley, & Bianchi, 2008). In
2004, approximately 30% of working American parents (both men and women) with children
5
under 18 usually worked on weekends rather than typical weekdays (McMenamin, 2007).
Based on the 2004 US Current Population Survey (US Department of Commerce, Bureau of
the Census, US Department ofLabor, & Bureau ofLabor Statistics, 2011) about 40% of
mothers working NS schedules reported child care as the main reason for working NS
schedules during the week (authors' own calculation). Australian Census data reveal that in
2007, in almost 60% of couples with children, either one or both parents typically worked
some hours between 7pm and 7am (ABS, 2009).
CONCEPTUAL FRAMEWORK
In this section we discuss theoretical perspectives that help explain the potential effect
of parental work schedules on children's well-being. We consider these theories to address
the following three critical questions: 1) Why NS work schedules might influence children's
development; 2) the plausible mechanisms (mediators) of this relationship; and 3) whether
this relationship is moderated by characteristics of the child and family. Figure 1 illustrates
the broad conceptual framework we developed from the relevant theoretical and empirical
literature to guide this review. Throughout the discussions about the influence ofNS work
schedules on children, standard (weekday, daytime) schedules are used as the comparison
group.
See Figure 1 (Appendix)
Ecological Theory
Bronfenbrenner's ecological theory (1979) conceptualizes child development as
occurring within nested settings. The microsystems (e.g., family, school, childcare center) are
the immediate settings in which a child is active, and are influenced by the mesosystems,
namely the interrelationships between microsystems. Children and their immediate settings
6
sit, in turn, within the exosystem that arguably includes the parental workplace, and they all
are situated within the context of the wider society and culture, the "macrosystem." Renamed
a bioecological theory (Bronfenbrenner, 2005), it has since been extended to highlight the
importance of genetic and other physiological characteristics and the continuous reciprocal
interaction that takes place between the person and environment over time.
Conceptual Resource Framework
Following Bronfenbrenner, Brooks-Gunn and her colleagues (Brooks-Gunn, Brown,
Duncan, & Moore, 1995) have operationalized the bioecological model in terms of familial
and extra-familial resources and have developed a conceptual resource framework that
integrates multidisciplinary perspectives (e.g., economists, sociologists, social demographers,
developmental and clinical psychologists, and pediatricians). In broad terms, four categories
of familial resources are thought to be critical for parenting and early socialization. These
include income, time, human capital (e.g., parental education, together with special skills,
training, and other characteristics), and psychological capital (e.g., the mental health of the
parents, the quality of their relationships, the psychological importance to them of factors
such as education and work, and beliefs about the parental role in childrearing). Extrafamilial resources include child care settings, schools, peer groups, community, and wider
social contexts (Kendall & Li, 2005). If the family engages with these community resources
appropriately, they constitute social capital, another important resource for children's
development. Brooks-Gunn and co-authors also focused on the issue of decision-making and
the choices parents face about allocating limited resources (Brooks-Gunn et al., 1995). They
later acknowledged that the conceptual framework did not account for the development of the
human capital of the child, the continuous reciprocal interaction ofwhich Bronfenbrenner
spoke that explains why children are often resilient within the context of a poor or
7
dysfunctional family (Brooks-Gunn, 1995). Optimal child health and development is,
therefore, a function of the quantity, quality and mix of familial and extra familial resources,
the decisions parents make regarding the allocation of their resources, and the characteristics
of the children themselves.
Based on bioecological theory and the conceptual resource framework, we have
devised the following model to guide our review (Figure 1), showing the key concepts, their
indicators, and linking paths. Structural factors that have contributed to the emergence of the
24/7 economy (Path A) are technological and demographic change, globalization, and labor
market deregulation (Dockery et al., 2009; Presser, 1999, 2003; Strazdins, Korda, Lim,
Broom, & D' Souza, 2004). Based on bioecological theory, we view the workplace as an
important part of the exosystem within which children grow and develop. Hence, parents' NS
work schedules, as a distal factor, are likely to influence children's development (Path B).
From the point ofview of the conceptual resource framework, parents' NS work schedules
may influence their children's development through their impact on familial resources, such
as income, parental time available for children, parental physical and psychological wellbeing, and the quality of the marital relationship (Paths C and D). According to the
framework, parents who choose to work NS schedules may decide to trade-off income and
time with their children for the potentially negative consequences that working NS schedules
may bring. Whereas working NS schedules, particularly night and evening shifts, may enable
more parent-child time during the day, such schedules can lead to fatigue and stress and
hence reduce parents' physical and psychological capacity for providing quality parenting
(Heymann, 2000). Similarly, if parents choose to work NS schedules to increase their
income, it may mediate a positive effect ofNS schedules on child outcomes; however,
physical and psychological tolls associated with working such schedules may offset this
effect. NS work schedules also likely influence child development through family processes,
8
such as parenting, parental-child relationship and home environment. The impact ofNS work
schedules on children may vary by the developmental age and gender of the child, the gender
of parents, and family characteristics (Path E). These moderators may also modify the
indirect effect ofNS work schedules on child development via the mediators (Paths F and G).
Below we discuss the mediators and moderators in more detail in light of relevant theoretical
and empirical literature.
Mediators (pathways linking parental NS work schedules to child development)
Previous studies have documented associations between working NS schedules and
the physical and mental health of workers, including working parents, although results are by
no means consistent. NS schedules, especially regular night shifts and rotating shifts, disturb
the body's circadian rhythms, alter physiological functions, and potentially lead to chronic
health conditions, anxiety, neurotic disorders and depression, and chronic sleep deprivation
and fatigue (Barnett, 2006; Kantermann, Juda, Vetter, & Roenneberg, 2010; Totterdell, 2005;
Vogel, Braungardt, Meyer, & Schneider, 2012). Working evening or night shifts (but not
rotating shifts) has been associated with greater depressive symptoms among mothers and
fathers (Perry-Jenkins, Goldberg, Pierce, & Sayer, 2007).
Mental and physical health is an important resource for parents because they influence
child health and development through their impact on family processes. Fatigue due to sleep
deprivation and mental stress associated with working NS schedules can reduce the quality of
time spent with children in developmentally important activities, and it can also lower the
quality of parenting and the home environment. The stress associated with NS work
schedules may adversely affect family dynamics and increase work-family conflict (Barnett,
Gareis, & Brennan, 2008; Davis, Goodman, Pirretti, & Almeida, 2008; Liu, Wang, Keesler,
9
& Schneider, 2011) and marital instability, especially in association with night shifts (Davis
et al., 2008; Kalil, Ziol-Guest, & Epstein, 2010; Presser, 2003).
Some studies have reported that parents who work NS schedules spend more time
with their children and are more likely to be present when children return home from school
(Wight et al., 2008), but other studies have found that working NS schedules is generally
associated with less time spent with children (Connelly & Kimmel, 2011; Rapoport & Le
Bourdais, 2008). Further, parents working NS schedules generally spend less time with
children in developmentally important activities, such as helping with homework and
attending parent-teacher meetings or school plays, than those working standard hours (Wight
et al., 2008). Previous research has also shown that, compared to standard work hours,
working NS schedules was associated with insensitive and harsh parenting practices
(Grzywacz, Daniel, Tucker, Walls, & Leerkes, 2011) and a decrease in the quality of the
home environment, especially in low-income families (Heymann & Earle, 2001).
Moderators
Most developmental perspectives (including bioecological theory and the conceptual
resource framework) emphasize that the nature and strength of influences on children's
outcomes will depend on the children's age, developmental status, and needs. Attachment,
psychoanalytic, and family theorists have emphasized the importance of the parent-child
relationship in developing children's trust and a sense of identity, and have drawn attention to
the importance of age-related transitions in developmental capabilities (Sroufe &Waters,
1977; Thompson, 2006). Infants and toddlers require a large investment of time and effort
from a primary caregiver to meet their physical needs and form a secure attachment. As
toddlers, they require constant supervision and activities focused on language development,
including reading time with their parents. Parents are invaluable in helping young children to
10
understand and express language, develop a variety of skills, and solve cognitive tasks
(Bradley, 2002). Further, parents aid in the development of emotional capacities, such as
regulating emotions, dealing positively with frustration, and delaying gratification (Eisenberg
& Valiente, 2002). Thus, the early years constitute an important developmental stage for
examining the impact ofNS work schedules on children's development due to schedulerelated parental stress and fatigue.
During middle childhood and adolescence, parental NS schedules may exert an
influence on different developmental domains and through different mechanisms, such as
parent-child closeness and supervision. These later years mark a time of important changes
related to school entry and transitions, as well as developmental advances that establish
children's sense of identity and their relationships with parents and peers (Eccles, 1999).
Adolescence is an important developmental stage in which young people begin engaging in
risky behaviors. Thus, parental supervision and monitoring may be just as important during
these late developmental stages as in early childhood.
Given the different developmental needs of boys and girls (Shonkoff & Phillips,
2000), the association between parental work schedules and child well-being may vary by
child gender. Boys have higher levels of activity than girls but they are less able to regulate
attention and control impulses (Else-Quest, Hyde, Goldsmith, & Van Hulle, 2006). They also
manifest higher levels of direct aggression, associated with externalizing behavior, poorer
peer relations, and lower pro-social behavior than girls (Card, Sawalini, Stucky, & Little,
2008). Thus, boys may be more affected by parental stress associated with NS work
schedules than girls. Boys also appear to have more adverse cognitive outcomes than girls if
their mothers were employed for more than 30 hours per week while they were infants
(Brooks-Gunn, Han, & Waldfogel, 2002). Similarly, heightened sensitivity to increased
maternal work hours has been observed in adolescent boys, relative to girls, in low-income
11
families (Gennetian, Lopoo, & London, 2008). Studies of dual-earner families with schoolaged children also suggest a stronger association between parental work demands and poor
monitoring for boys than girls (Bumpus, Crouter, & McHale, 1999; Greenberger, O'Neil, &
Nagel, 1994).
Parental gender adds another dimension to the complex relationship between NS work
schedules and child outcomes due to gendered pathways between parenting and child
outcomes (Lamb, 2010; Laursen & Collins, 2009; Raley & Bianchi, 2006). Because parents
tend to engage in more activities with same-gender children (e.g., fathers and sons), it is
likely that fathers' absence due toNS work schedules has a larger detrimental effect on boys
than girls. Fathers' long work hours (55 hours or more per week) have been associated with
higher levels of externalizing behaviors in boys than girls (Johnson, Li, Kendall, Strazdins, &
Jacoby, 2013).
The association between NS work schedules and child outcomes may also differ by
the gender of parent due to differential sharing of child care and household work
responsibilities. Despite increases in the proportion of women entering the labor force,
women remain largely responsible for family life (Maume, 2011; Maume & Sebastian, 2012).
Women working NS schedules report higher levels of sleep deprivation and work-to-family
conflict than their male counterparts (Maume & Sebastian, 2012; Tuttle & Garr, 2012), and
work-to-home conflict has a negative effect on marital quality in women but not in men
(Maume & Sebastian, 2012). This suggests that maternal NS work schedules may exert a
larger effect on the family and children than paternal shift schedules.
NS work schedules present parents with both advantages and challenges in balancing
work and family demands. Whether or not a parent chooses (or can choose) to work NS
schedules is likely to moderate the effect ofNS schedules on both family processes and child
outcomes. We know that some parents choose to work such shifts in order to spend the day
12
with their young children (Garey, 1999), whereas for others working non-day shifts is a job
requirement (Presser & Cox, 1997). In the former case, any physical or mental stress
associated with working non-day shifts might be offset by parents' satisfaction with their
ability to spend time with and take care of their children (Garey, 1999). In the latter case,
stress, parental depression, and marital instability induced by working NS schedules, as well
as the physiological tolls (e.g., fatigue and interrupted sleep patterns) of such schedules,
could adversely affect the child's well-being (Heymann, 2000).
Family structure and income constitute another potential moderator of the NS work
effects on child outcomes. It is well established that socioeconomic disadvantage, such as
living in a single-parent, low parental education and low-income family, is associated with
poor child health and developmental outcomes (Hertzman, 1999; Keating & Hertzman,
1999). These factors may exacerbate any negative effect ofNS work schedules on child
development. Families with more social and economic resources may be better able to cope
with challenges presented by NS work schedules and may even benefit from working such
schedules, especially when parents chose to work these schedules. In 376 dual-earner
middle-class families, Davis, Crouter, and McHale (2006) found higher levels of adolescentreported intimacy with mothers when their mothers worked NS hours, compared to when
they worked standard hours, perhaps because these shifts meant that they could spend more
quality time with their children.
Family characteristics other than income and family structure may also modify the
impact ofNS work schedules on family processes and thus on child development. Such
characteristics are diverse and are often better captured in qualitative research. Small-scale
qualitative studies of nurses suggest that their families adapt toNS work schedules quite well
and in some respects they even benefit from shift work. For example, in a study by Barnett
and Gareis (2007), 8-14 year old children of mothers working an evening shift as nurses rated
13
their fathers as having greater awareness of their activities and better parenting skills, and
they themselves were more likely to disclose information to their fathers. Thompson' s study
of night working nurses and their families in the UK also reveals that mother's absence due to
work allowed the father to take on more child care and other domestic responsibilities
(Thompson, 2009). Thus maternal NS schedules may draw fathers into closer care
relationships with children and generate less gender stereotyped family interactions (McHale,
Crouter, & Whiteman, 2003). However, to fulfil the gendered expectations to be "good"
wives and mothers, the women in the Thompson study attempted to mitigate any potential
negative impact of working night shifts on their families, at the expense of their own wellbeing, in the form of significant reductions in their own sleep duration, worse mood, and
reduced alertness (Thompson, 2009).
This paper represents the first comprehensive and critical assessment of existing
research evidence linking parents' NS work schedules to child development. The paper
makes three key contributions to the field: development of a new conceptual model to guide
the review; a synthesis and critical assessment (based on theory and on multiple
methodological criteria) of the diverse research findings on the topic; and theory- and
evidence-based recommendations for future research.
METHODS
This review focused on studies that directly examined the link between parents' NS
work schedules and child mental, physical, and cognitive development. The search included
peer-reviewed journal articles and books on this topic and was restricted to the literature from
English-language sources in developed countries from 1980 to December 2012. We identified
the majority of the studies through an electronic search in ProQuest, Web of Knowledge,
Science Direct, PsyciNFO, and OVID Medline.
14
We searched for broad key words and their combinations in the title of the article
(nonstandard work, nonstandard hours, work schedules, shift work, night work, evening
work, and weekend work), together with terms identifying outcomes anywhere in the full text
of the article (mental health, behavior, overweight, obesity, body mass index (BMI),
cognition, sleep, well-being, and child or adolescent). The initial search produced 364 records
(See Figure 2). Using the reference lists of these articles and the web pages of some authors
and professional associations to extend the search, we identified an additional three studies.
After removing duplicate records, 241 records remained that were potentially relevant. An
assessment of the titles and abstracts of these records against the selection criteria (examining
a direct link between parental NS schedules and child developmental outcomes) resulted in
24 articles that we read in full. We excluded just one article after assessing the full text of the
24 studies because it did not examine a direct link between work schedules and child
outcomes (Barnett & Gareis, 2007), leaving 23 studies in the final review. Many of the
excluded articles focused on adult health and well-being outcomes, including sleep
disturbance (n = 94), or family outcomes such as time spent with children, parenting quality,
parent-child closeness, marital stability, and the home environment (n = 32) in respect toNS
work schedules; and some of the other excluded studies focused only on the prevalence and
determinants ofNS work schedules. While not reviewed, we discussed the studies that
examined the relationship between NS work schedules and family processes in both the
introduction and discussion to facilitate our understanding of the pathways through which NS
work schedules may influence child development.
See Figure 2 (Appendix)
We did not use a fixed definition ofNS schedules as a selection criterion as there is
no one single definition in the literature and by doing so we would have omitted a significant
15
number of relevant studies. The studies based on US national datasets typically define NS
schedules as hours worked outside 6am- 6pm on the main job, with evening shifts sometimes
defined as 2pm- 9pm and night shifts as 9pm- 8am (e.g., Han, 2008; Han & Miller, 2009;
Han, Miller, & Waldfogel, 2010). Studies based on the Canadian National Longitudinal
Study of Children and Youth (NLSCY) and the Household, Income and Labour Dynamics in
Australia Survey (HILDA) defined self-reported worked schedules on the main job, including
regular evening shifts, regular night shifts, irregular hours, and split or rotating shifts or
weekends, as NS schedules (Dockery et al., 2009; Strazdins, et al., 2004; Strazdins,
Clements, Korda, Broom, & D'Souza, 2006). Due to substantial diversity in the way both
NS work schedules and child outcome variables were measured (e.g., mental health,
behavioral difficulties), we undertook a comprehensive review of the extant published
literature rather than conducting a meta-analysis.
Evaluation Criteria
We employed five methodological criteria to present the findings of the studies
reviewed (see Appendix ): (1) sample representativeness, (2) study design (longitudinal vs.
cross-sectional, (3) adequate control for a minimum set of socio-demographic characteristics
as confounders and covariates, (4) use of analytical methods to address selection bias, and (5)
examination of mediating and moderating factors. Study quality ratings, which ranged from 0
to 5, indicated the number of criteria met by the study as determined by the authors. The
most important issue we considered in rating the studies was the extent to which studies have
adjusted for potential selection bias. That is, we whether the observed associations between
NS work schedules and child outcomes could be attributed to other unobserved or omitted
factors associated with the likelihood of working NS schedules and having poor (or positive)
child outcomes. Comprehensively dealing with selection bias entails adjusting for major
16
known confounders and covariates using longitudinal data and employing such analytical
techniques as Ordinary Least Square (OLS) Regression, fixed effects modeling, or propensity
score matching. We consider a minimum set of key socio-demographic confounders and
covariates to be family structure, parental education and age, the number of parental work
hours, child gender and age, and the number of children in the household. Ethnicity was also
considered as key covariate to adjust for as appropriate. Some studies were based on a
predominantly homogeneous population, making this adjustment unnecessary (Strazdins et
al., 2004). In other studies using fixed effects models, all time-invariant covariates, such as
ethnicity or race, would have to be omitted.
See Table 1 (Appendix)
There are other sources of information bias, including self-reported outcome
measures, missing cases and loss to follow-up in longitudinal data collection. Because these
issues are inherent in non-experimental studies, such as those covered in this review, we did
not use these factors as a criterion to rate the studies. We have, however, paid particular
attention to research methodology that may also appropriately and adequately address
missing information and/or attrition issues. We have also addressed these common
methodological issues in the discussion section of this review.
RESULTS
Overview of the Results
The 23 studies that met the inclusion criteria (see Appendix) included 22 peerreviewed journal articles and one book, all based on non-experimental data. Seventeen
studies were based on a US sample, two studies used an Australian sample (Champion et al.
2012; Dockery et al., 2009), two analyzed data from a Canadian sample (Strazdins et al.,
17
2004, 2006), and there was one study each from the UK (Barton, Aldridge, & Smith, 1998)
and Croatia (Radosevic-Vidacek & Koscec, 2004). Eleven studies were cross-sectional and
12 were longitudinal. Several studies were based on the National Longitudinal Study of
Youth-Child Supplement (NLSY-CS), a data set that may overrepresent children who were
born to young mothers with lower education and income (Chase-Lansdale, Mott, BrooksGunn, & Phillips, 1991). Three studies were based on data from the National Institute of
Child Health and Human Development Study of Early Child Care and Youth Development
(NICHD SECCYD), which may underrepresent children from disadvantaged families. The
age of the children across these studies ranged from birth to 20 years. Twelve studies
examined both parents' NS work schedules, ten focused only on mothers' NS work schedules,
and one study examined only fathers' work schedules (Barton et al., 1998). Mental health
and behavioral problems were the most common type of child outcome examined (15
studies). Four studies focused on cognitive development (Han, 2005; Han & Fox, 2011;
Heymann, 2000; Odom, Vernon-Feagans, & Crouters, 2013), three studies examined
children's body weight as the outcome (Champion et al., 2012; Miller & Han, 2008;
Morrissey, Dunifon, & Kalil, 2011), and one focused on children's sleep patterns (RadosevicVidacek & Koscec, 2004). Two of the 15 studies that examined mental health and behavioral
problems also analyzed school engagement and after-school activities as additional outcomes
(Han, 2006; Hsueh & Y oshikawa, 2007).
The 23 studies provided a range of unstandardized and standardized effect sizes (ES).
Wherever possible, a standardized ES was calculated from the published data to facilitate
comparisons (see Appendix). Of those that used multiple linear regression techniques, six
studies reported standardized beta coefficients(~), which can be interpreted as ES. In the nine
studies the authors provided unstandardized beta coefficients (b) and we calculated ES using
band standard deviations (SD) of the outcome variable (b/SD). Four studies using logistic
18
regression provided an odds ratio (OR). In two studies where the authors used structural
equation models (Han & Miller, 2009; Han et al., 2010), standardized beta
coefficients(~)
were reported that were equivalent toES. In two studies (Barton et al., 1998; RadosevicVidacek & Koscec, 2004), analyzes of variance (F test) statistics were reported.
On the whole, the effect sizes of parental NS schedules on children's behavioral and
cognitive outcomes were small by conventional standards, mostly < .20 (Cohen, 1988). The
significant effect sizes, however, were larger for preschool-age or younger children (ES = .20
- .35). In studies stratified by indicators of socioeconomic status, effect sizes were larger in
low-SES (Strazdins et al., 2004, 2006), low-income (Han, 2008; Han et al., 2010), and single
parent families (Dockery et al., 2009; Han & Waldfogel, 2007). Four studies analyzed only
low-income or low-wealth samples: two studies examined preschool-age children (Joshi &
Bogen, 2007; Odom et al., 2012), with small effect sizes for cognitive ability(< .20) and
medium effect sizes (unmediated ES = .36- .55) for behavioral outcomes; and two analyzed
school-age children (Dunifon, Kalil, & Bajracharya, 2005; Hsueh & Yoshikawa, 2007), with
a small effect size (mostly ES < .1 0). In studies that included both parents, the ES was
comparable for maternal and paternal work schedules, although the relative strength of
association varied by child age, SES and type ofNS schedule. The ES for BMI was also
mostly small,< .20 (Miller & Han, 2008; Morrissey et al., 2011). Miller and Han (2008)
found a considerable effect size for the number of years mothers worked a NS shift on child
BMI among families in the second income quartile (ES = 0.27).
Child Mental Health and Behavioral Problems
In this section, we summarize the findings with reference to the conceptual
framework presented in Figure 1. Although child age is included as a moderator in our
conceptual framework (Figure 1), because few studies had directly tested child age as a
19
moderator and because the majority of the studies analyzed the data separately by child age
group, we begin the discussion of the results separately for preschool and school-age children
and adolescents.
Preschool Children
Evidence from both cross-sectional (Gassman-Pines, 2011; Joshi & Bogen, 2007; Strazdins et
al., 2004, 2006) and longitudinal studies (Daniel, Grzywacz, Leerkes, Tucker, & Han, 2009;
Rosenbaum & Morrett, 2009) was consistent and suggests that young children with at least
one parent who worked NS schedules had more emotional and behavioral problems than
those whose parents worked standard schedules. The magnitude of the association was
similar for both mothers' and fathers' NS schedules (Strazdins et al., 2004, 2006).
Evidence suggests that exposure to parental NS work schedules in the child's first few
years of life is particularly detrimental. Mothers' or fathers' NS schedules in their child's
infancy were associated with more behavioral problems at ages 2 and 3, as compared to
parents with standard schedules (Daniel et al., 2009; Rosenbaum & Morrett, 2009). Two
studies found that evening or night shifts had the strongest and most consistent associations
with child behavioral problems, such as excessive fussiness and distractibility, as well as
internalizing and externalizing behaviors (Gassman-Pines, 2011; Rosenbaum & Morrett,
2009).
School-Age Children and Adolescents
The findings from two longitudinal studies that used representative samples and addressed
selection bias reported a significant association between the child's cumulative exposure to
parental NS work schedules and mental health and behavioral problems. Han (2008) found
that behavioral problems among 4- to 10-year-old children increased with the number of
years that mothers had worked a NS schedule. Similarly, Han and Miller (2009) reported that
the number of years mothers worked night shifts and fathers worked evening shifts was
20
significantly associated with higher risks of depression in children aged 13 or 14. Han et al.
(2010) found that the number of years mothers had worked a night shift was also linked to
adolescent smoking, drinking, drug use, delinquency, and sexual activity. Based on a sample
of low-income families (primarily single mothers), Hsueh and Yoshikawa (2007) found that
5- to 16-year-old children whose primary caregiver worked variable NS schedules had more
teacher-reported externalizing behaviors but fewer parent-reported internalizing behaviors
than children whose caregivers did not work such hours.
In contrast, Dunifon et al. (2005) reported no association between parental NS
schedules and behavioral problems in 372 children aged 5-15 whose mothers were receiving
cash assistance in an urban Michigan county.
Mediating Factors
Studies that have examined pathways linking NS schedules with child behavioral problems
reported that mediating factors include parental depressive symptoms (Daniel et al., 2009;
Rosenbaum & Morrett, 2009; Strazdins et al., 2006), poor parenting and parental supervision
(Han et al., 2010; Strazdins et al., 2006), reduced parent-child closeness and less time spent
with children (Han & Miller, 2009; Han et al., 2010; Rosenbaum & Morrett, 2009), and a less
supportive home environment (Han & Miller, 2009; Han et al., 2010; Han & Waldfogel,
2007). Of note, Han et al. (20 10) found that irregular shifts were associated with greater
parental knowledge of child's whereabouts, which, in turn, reduced risks for adolescent risky
behavior. The authors speculated that families with parents who worked irregular shifts were
of higher SES in this particular NLSY sample, and therefore may have chosen these
schedules to meet their child care or family needs.
Moderating Factors
Whereas the majority of the studies adjusted for child gender in their analyses, few
specifically examined child gender as a moderating factor. Whereas Han et al. (2010) found
21
that adolescent boys were more likely than girls to engage in risky behavior due to
cumulative exposure to mothers' night shifts, two studies based on small local samples found
that girls were more negatively affected by parents' NS work schedules (Barton et al., 1998;
Joshi & Bogen, 2007). With regard to family structure, there is consistent evidence from
three studies based on large samples that children of single-mothers tended to have more
problems associated with NS work schedules than those living in two-parent families
(Dockery et al., 2009; Han, 2008; Han & Waldfogel, 2007). Similarly, there is a consistently
stronger association in low-SES families than in middle- or high-SES families (Han, 2008;
Strazdins et al., 2004, 2006). Han (2008) found a stronger relationship between the number of
years a mother had worked NS schedules and poorer behavioral outcomes in 4- to 10-yearold children who either lived in single-mother or low-income families, whose mothers
worked in cashier or service occupations, or whose mothers worked non-day shifts full-time.
Child Cognitive Development
Four studies have assessed cognitive outcomes in respect to parental NS work
schedules. In a US sample, Han (2005) found that children of mothers who worked NS
schedules in their first year oflife had poorer cognitive outcomes two to three years later,
although the results varied by dimensions of cognitive performance, timing and length of
exposure to these schedules. Children had lower scores on the Mental Development Index
(MDI) at 24 and 36 months, and significantly lower verbal comprehension and expressive
language skills at 36 months, if their mother had worked a NS schedule in the first year of life
but not in the second or third year. Using data from the NLSY-CS, Heymann (2000) found a
higher proportion of school-aged children with poorer outcomes in mathematics, vocabulary
and reading if parents worked evenings or nights. Based on the same dataset but using
growth-curve modeling, Han and Fox (2011) found that the number of years a mother worked
22
a night shift was associated with lower reading scores, and the number of years she worked
evening or night shifts was associated with lower progress in math skills between ages 6 and
14 . Having a father who worked more years at an evening shift was also associated with
reduced mathematic scores. The authors' mediation analysis suggested that eating meals
together, parent knowledge of children's whereabouts, and some after-school activities were
plausible explanations for these associations (Han & Fox, 2011 ). In a US sample of 250
African American children (aged 24 to 36 months) born to mothers residing in low-income
and rural counties in North Carolina and Pennsylvania, Odom and co-authors found that
mothers' NS work schedules at 24 months were associated with lower expressive language
ability at both 24 and 36 months (Odom et al., 2013). These associations were mediated
through negative maternal interactions with their children and negative work-family
spill over.
Childhood BMI
Analyzing data from the NLSY-CS, Miller and Han (2008) found that the BMI of 13to 14-year-old American children increased significantly if mothers worked either a few(< 4)
or many (10 or more) years ofNS schedules. This relationship was stronger among the "near
poor" (i.e., families in the second quartile of family income, a level of income where families
could not qualify for a number of public assistance programs yet tend to have substandard
living), compared to families in other income quartiles. In a largely representative sample of
434 children born to Caucasian women in Adelaide, South Australia, Champion et al. (2012)
reported that fathers' NS work schedules (shift schedules, evenings, nights, and weekends)
were associated with increased odds of child overweight and obesity. In contrast to other
studies on the topic, mothers' NS work schedules were not significantly associated with the
outcome variables examined. However, when both parents worked NS schedules the
23
investigators found an increased risk for child overweight and obesity. Due to the study's
cross-sectional design and the fact that all types ofNS work schedules were combined into
one category, the findings reported by Champion et al regarding mothers' NS work schedules
need to be interpreted with caution.
Using longitudinal data from the NICHD SECCYD and within-child fixed-effect
models, Morrissey et al. (2011) found no significant association between maternal NS work
schedules and child BMI among 990 American school children aged 8 to 12. However, the
NICHD SECCYD sample is not nationally representative, with 80% of the children living in
two-parent families and more than 75% in higher-income families.
Other Outcomes
Two of the 15 studies that examined child behavioral problems (already reviewed
above) also examined children's school engagement (Han, 2006; Hsueh & Y oshikawa, 2007)
and involvement in extracurricular activities (Han, 2006) as additional outcomes. One study
focused on child sleep patterns (Radosevic-Vidacek & Koscec, 2004). These studies found
that children tend to have lower levels of school engagement, attend fewer extracurricular
activities, and sleep less when their parents work NS hours. The studies provided no
information, however, about the mechanisms that might underpin this association. Whereas
parents working NS hours (e.g., evenings or nighttime) are available during daytime when
outside school activities take place (3pm-6pm), they may not have sufficient energy to take
their children to such activities or may lack time to do so due to the competing demands of
housework, such as preparing meals before they go to work in the evening. It is possible that
disrupted family processes or child mental health and behavioral problems associated with
NS work schedules may affect the child's sleep and school engagement.
24
DISCUSSION
Guided by our conceptual framework, we examined studies that investigated the
associations between parents' NS work schedules and four child developmental outcomes
(internalizing and externalizing problems, cognitive development, and body mass index) and
three other related outcomes (sleep pattern, school engagement, and extracurricular
activities). Of 23 studies reviewed, 21 studies reported a statistically significant negative
association between NS work schedules and at least one child developmental outcome. Thus,
the majority of the studies support our general hypothesis that parental NS work schedules, as
a distal factor or part of the "exosystem" in which children grow and develop, have negative
consequences for the developing child with regards to mental health and behavioral
problems, cognitive development, overweight and obesity, and other related outcomes.
Two studies that did not find a significant association between NS work schedules
and child outcomes were Dunifon (2005) and Morrisey (2011) and their respective
colleagues, although both studies were based on longitudinal data and used child fixed effects
models to address potential selection bias. Dunifon et al. (2005) examined behavioral
problems in a small sample of children from low-income families (N = 372, ages 2 -15) and
found no effect ofNS work schedules on child behavioral problems. In contrast, Han (2008)
analyzed a large longitudinal national data set that over-represented less advantaged families
(US NLSY-CS, N;::::; 7,000, ages 4- 10), and reported a significant association between the
number of years mothers worked NS schedules and behavioral problems in children,
particularly in low-SES families. A child fixed effects model was also used in this study.
Morrisey et al. (2011) did not find a significant relationship between NS schedules and child
BMI in a sample of US children (NICHD SECCYD N = 990, ages 8-12) in which lowincome families were underrepresented. In contrast, Miller and Han (2008) also analyzed
longitudinal data and used child fixed effects models to address selection bias, but they
25
reported a significant association between NS schedules and child BMI in a large sample of
teenage children (ages 13-14). These differing results may be in part attributed to the size and
the characteristics of the population under investigation, and different constellations of
factors adjusted in the studies.
Findings regarding child gender differences in the effect ofNS work schedules on
child behavioral outcomes differed by study quality. Highly rated studies (meeting all five
criteria) reported that adolescent boys were more likely than girls to engage in risky behavior
due to their cumulative exposure to mothers' night shifts (Han et al., 2010), but two crosssectional studies based on small local samples (meeting only two of the five criteria) found
that girls were more negatively affected by their parents' NS work schedules (Barton et al.,
1998; Joshi & Bogen, 2007).
The most consistent associations were reported among preschool-age children for
both cognitive and mental health/behavioral problems, and among adolescents for risky
behaviors. These findings suggest that parental NS work schedules matter for both early and
later developmental stages but in different developmental domains. Consistent with our broad
conceptual framework, there is evidence that the negative associations between NS work
schedules and child behavioral problems are partly mediated through family resources, such
as parental psychological capital (e.g., depressive symptoms) (Daniel et al., 2009;
Rosenbaum & Morrett, 2009; Strazdins et al., 2006), family processes such as low quality
parenting (Han et al., 2010; Strazdins et al., 2006), reduced child-parent interaction and
closeness (Han & Miller, 2009; Han, et al., 2010; Rosenbaum & Morrett, 2009), and a less
supportive home environment (Han & Miller, 2009; Han et al, 2010; Han & Waldfogel,
2007). We should be cautious, nevertheless, about concluding that maternal depressive
symptoms constitute a mediating factor, as in almost all studies ofbehavioral problems that
focused on young children (age 0-10) child mental health/behavioral problems were
26
measured with mother-reported ratings (e.g., CBCL, BPI), which are likely to be influenced
by the mothers' mental health.
As expected, some of the studies reviewed have shown that associations between NS
work schedules and child developmental outcomes differ by family SES. For example, based
on studies that addressed selection bias and controlling for key confounders and covariates,
there is clear evidence that associations between parents' NS work schedules and child
outcomes are more pronounced in low SES families (e.g., low-income, single-parenthood,
and low occupational status). This evidence is demonstrated in studies that found significant
interactions between SES and NS work schedules (Dockery et al., 2009; Han, 2008; Han &
Waldfogel, 2007; Strazdins et al., 2004, 2006) when mental health and behavioral problems
were examined. These findings suggest that families with more economic resources and
human capital may better be able to meet the challenges ofNS work schedules than less
advantaged families. The association between NS work schedules and child outcomes is also
magnified when parents work NS schedules on a full-time basis, compared to working these
schedules on a part-time basis. These findings suggest that evening and night shifts are
particularly detrimental to child developmental outcomes (Daniel et al., 2009; Han & Fox,
2011; Han & Miller, 2009; Rosenbaum & Morrett, 2009). Further, cumulative exposure to
NS work schedules has a negative impact on child developmental outcomes (Han, 2008; Han
& Fox, 2011; Han & Miller, 2009; Miller & Han, 2008), thus underscoring the importance of
using longitudinal data in future inquiry.
Strengths and Limitations of Reviewed Studies
The robustness of the evidence provided by the studies reviewed depends on their
methodological rigor. The majority were based on large and/or representative samples,
controlled for key confounders, and examined moderating and mediating factors, thus
27
providing in-depth information about the link between NS work schedules and child
developmental outcomes. There were, however, a number of limitations.
Cross-Sectional Data
Due to the nature of the topic, experimental data were not a possibility and thus a causal
relationship between parental NS schedules and children's well-being is difficult to establish.
Whereas it is encouraging that 12 out of 23 studies used a longitudinal design, ten studies
were based on cross-sectional data, thus precluding inferences about NS work schedules as a
causal factor for child well-being, and raising a concern about reverse or reciprocal causality.
For example, it is possible that parents arrange their work schedules as a way of managing
children with more behavioral problems. In addition, the measurement of work schedules at
one point in time does not provide information about how long children have been exposed to
these work patterns and the changes that may have occurred over time. Use of longitudinal
data would reveal whether or not, or to what extent, the any disadvantages associated with
NS schedules found at one time point persists over time. Longitudinal studies reviewed to
date have begun to consider both the onset and duration of children's exposure to parents' NS
work schedules (Han & fox, 2011; Han & Miller, 2009; Han et al., 2010). We call for many
more studies in the future to take a longitudinal approach.
Less Information about Father's Work Schedules
We were pleased to see that 13 out of the 23 studies examined fathers' work schedules.
However, the remaining ten studies did not do so, primarily due to lack of data. The
association between NS work schedules and child outcomes may differ by the gender of the
parent due to gender differences in sharing child care and household work responsibilities
and also gender differences in occupations. With an increasing emphasis on paternal
involvement in children's development, the field will benefit from giving equal attention to
the work schedules of both mothers and fathers, and, in particular, joint work schedules in
28
dual-earner families. One cross-sectional study examined joint NS schedules worked by both
parents in 434 nine-year-old children and found that these schedules were associated with
child overweight and obesity, but with a weak statistical significance. The small sample size
and the cross-sectional design limited the generalization of this study. Given that fathers tend
to provide more child care than normal when mothers work NS schedules (Barnett & Gareis,
2007; Thompson, 2009), it is important to understand how both mothers' and fathers' work
schedules may independently or jointly shape children's development. Indeed, the evidence
from the studies that examined both mothers' and fathers' NS work schedules suggests that
both parents' NS schedules matter (Champion et al., 2012; Han & Fox, 2011; Han & Miller,
2009; Rosenbaum & Morrett, 2009; Strazdins et al., 2004, 2006). Whereas maternal work
schedules (particularly night shifts) appear to be more strongly linked to child well-being, the
type ofNS schedule each parent works has differential but significant associations with child
outcomes. Maternal night shifts and paternal evening shifts had the most consistent negative
associations with child and adolescent mental health issues (Han & Fox, 2011; Han & Miller,
2009; Han et al., 2010). Unfortunately, most of the existing large datasets do not have as
detailed information about fathers as on mothers. We call for future data collection efforts to
overcome this common limitation.
Lack ofData on Child Care and Choice ofNS Work Schedules
Most studies lacked information about the availability and quality of child care available to
parents working NS schedules. The studies examined also lack precision as to measurements
of the timing of child care arrangements that can be matched to the timing of parental work
schedules. The impact of parental NS schedules on children may depend on the availability,
affordability and quality of care arrangements. For example, formal care for children is rarely
available outside standard business hours and weekdays. Children whose mothers work NS
schedules are more likely to be cared for by fathers in two-parent families or by other
29
relatives or non-relatives in a single-mother family (Han, 2004). When both formal and
informal supports are absent, parents working NS schedules may have great difficulties in
juggling work and family demands. This is a particularly important issue for single-parent
families and a plausible explanation for the findings from this review that the adverse
association between NS schedules and child outcomes is stronger in single-parent families.
The quality of child care also matters. Previous research has shown that high quality child
care has a long-term positive impact on children's development (Kohen, Hertzman, &
Willms, 2002). With the passage of the US federal welfare reform law, many low-income and
single mothers have no choice but to place their young children at low quality childcare
facilities, which may impair their children's development (Chaudry, 2004). Socially
disadvantaged families may be more likely to use poor quality child care when working NS
schedules. Hence child care quality is a plausible mechanism linking NS schedules to poor
child well-being and warrants future inquiry.
Closely tied to child care is the issue of whether parents choose to work NS schedules
or have job flexibility in order to meet family and child care needs. These issues were not
considered in the majority of studies reviewed. NS work schedules may present advantages to
both-parent families where parents are able to choose work schedules to meet their child care
needs and to enable fathers' greater participation in parenting (Barnett & Gareis, 2007;
Thompson, 2009). Indeed, some parents choose to work NS schedules as a way of spending
more time with their children (Hattery, 2001). Working mothers with flexible schedules tend
to spend more time in direct child care but less time in shared leisure activities (Rapoport &
Bourdais, 2008). However, it is unclear if the choice of flexible NS schedules benefits
children's mental health and cognitive development. Parents who choose to work flexible NS
schedules may still be prone to stress and fatigue associated with NS schedules. Tuttle and
Garr (2012) have shown that women working shift work have greater work-to-family conflict
30
than men, even when women have more control over their work schedule. It is important for
future research to take this issue into consideration. Recent welfare reform in the US has seen
a great number of low income single mothers move into poor quality jobs that require
inflexible NS schedules (Jones-DeWeever, Peterson, & Song, 2003; Presser, 1999; Presser &
Cox, 1997).
Reliance on Parent-Reported Measures of Child Behavioral Outcomes
There is considerable research on the concordance between parent- and child/adolescentreported measures ofbehavioral problems. However, there is no evidence that child-reported
measures are more accurate than those reported by their parents. The accuracy of reported
child behavioral problems is influenced by the saliency ofbehavioral problems to parents and
children, and the willingness of both to report these problems (Karver, 2006). The accuracy
of self-reports may also differ by the relevance of the problems to a specific setting (home
versus school) and the parent's gender. The literature recommends employing multiple
informants when collecting information on child and adolescent behavioral problems
(Karver, 2006; Salbach-Andrae, Lenz, & Lehmkuhl, 2009; Seiffge-Krenke & Kollmar, 1998).
Child-reported measures ofbehavioral problems should be collected in studies that
involve older children who are able to answer the questionnaire. Out of all 15 studies of
mental health and behavioral problems, 11 involved school-aged children and adolescents,
but only five of these used child-reported measures ofbehavioral outcomes, and the other six
studies analyzed samples combining young and older children (ages 2-16). While motherreported measures may be considered practical for young children (ages 0-5) in these studies,
such measures can be complemented or enriched by a secondary carer (e.g., child care centre
or kindergarten or preschool teachers, fathers, grandparents or nannies). Further, mothers
may be biased either downward or upward in their assessment of their children's behavior,
particularly when maternal mental health is a concern (Sawyer, Streiner, & Baghurst, 1998).
31
Hsueh and Y oshikawa (2007) have shown that parental NS schedules were associated with
teacher-reported child behavioral problems but not with mother-reported child behaviors.
Other Sources ofInformation Bias
Self-reported measures, missing cases and loss to follow-up are also potential sources of
information bias. None of the four studies that examined child cognitive outcomes, and none
of the three that examined adolescent body weight, used self-reported outcome measures.
Instead objective measures were used, including cognitive and language test scores and body
weight and height. However, in all 15 studies of child behavioral problems, parent-, teacheror child-reported outcome measures were used. Self-reporting is unavoidable in both clinical
and non-clinical studies that examine mental health and behavioral problems. For example,
well-established instruments, such as the Kessler Psychological Distress Scales (Kessler et
al., 2002), the Beck Depression Inventory (Beck, Steer, & Carbin, 1988), the Child Behavior
Checklist (Achenbach, 1991), and the Behavior Problems Index (Zill, 1990) are all based on
data collected from self-reports. As discussed above, one way of minimizing potential bias is
to collect information from multiple informants (child/adolescent, mother, father, teacher, and
secondary cares). Missing cases and loss to follow-up are also a source of potential
informational bias and are common problems with survey and cohort data. The vast majority
of the studies covered in this review utilized such data. To the extent that low SES groups are
often over-represented in missing cases and in loss to follow-up (Li, Kendall, Henderson,
Downie, Landsborough, & Oddy, 2008), the negative effects ofNS work schedules on child
outcomes are likely to be underestimated.
FUTURE DIRECTIONS
Parental work is an important social determinant of child health and wellbeing, especially in
the era of changing economic dynamics and an increasingly globalised economy. In
32
particular, occupations that require employees to work NS schedules, such as in the service
sector, are expected to account for proportionally high job growth in the future (US Bureau of
Labor Statistics, 2012). The findings from the studies reviewed have shown that NS work
schedules exert a larger negative impact on children from low SES backgrounds than on
children from families with more resources. This has important implications for
understanding well-established social gradients in child health and development (Keating &
Hertzman, 1999). Poor working conditions, including parental NS schedules, are a plausible
mechanism mediating these social gradients and disparities in child developmental outcomes.
Therefore, the impact of parental NS work schedules on children's developmental outcomes
warrants more fine-grained research. This line of enquiry also needs greater guidance by a
theoretical framework that recognises broader societal and community influences and
considers the characteristics of parents and the child at different developmental stages. Below
we discuss a number of issues for future investigators to consider.
Links between NS Schedules and a Broader Range of Developmental Outcomes
Most studies to date have focused on behavioral and mental health outcomes, only
four have examined children's cognitive development, and only three have investigated
obesity. Much more research is needed to enhance our knowledge about the relationship
between NS work schedules and child cognitive outcomes, particularly academic
achievement in school-age children. Further research is also needed not only to examine the
link between NS work schedules and child BMI but also to investigate whether and how
proximal factors, such as nutrition and physical activity, may also be influenced by NS work
schedules. Based on the conceptual resource framework, we would expect parental NS work
schedules to influence these developmental outcomes through the pathways of time available
for the use of family and psychological capital (i.e., parental mental health and the quality of
33
the relationships between the parents themselves and with their children). It is also plausible
that these various developmental outcomes are interrelated contemporaneously or
longitudinally. With the use of more rigorous research design and advanced modelling, it will
be possible to examine various developmental outcomes of children who are exposed to
parental NS work schedules over time. This would help researchers determine ifbehavioral
and cognitive development in early childhood leads to mental health problems and risk-taking
behavior in teenagers, relative to children whose parents work standard daytime schedules.
The field will also benefit from more research addressing the important issue of whether or
not the association between parental NS work schedules and early child development will
persist or dissipate over time.
Better Specification ofNS Work Schedules
Some of the studies reviewed have shown that night shifts were associated with poor
cognitive and behavioral outcomes among young children, and with higher levels of
depression and more risky behaviors among adolescents. On the other hand, two studies
reported that irregular or variable shifts were associated with reduced adolescent risk-taking
behaviors (e.g., smoking, drinking, and using drugs) via improved parental knowledge of
their child's whereabouts (Han et al., 2010; Han & Waldfogel, 2007). We note, however, that
the data (NLSY-CS) used in these studies suggested that parents who reported having
irregular shifts tended to choose such schedules and/or have some control over the time when
they worked. Rotating and irregular shifts would have less predictable effects on parental
time at home, which might make it harder for families to plan and attend events together.
These shifts, nevertheless, can be beneficial to children if the shifts are employee-initiated
rather than required by employers (Henly, Shaefer, & Waxman, 2006). Such findings
highlight the importance of distinguishing between the evening, night, rotating, irregular or
34
weekend work of mothers and fathers and of taking into account whether parents choose
these shifts.
Often researchers have collapsed different types ofNS schedules into one single
category due to inadequate sample sizes in each group. As noted by other scholars in the
field, such an analytic strategy limits our understanding about which schedules influence
child development and family processes (Barnett, 2006; Presser, 2003). Further, no studies
have considered the location ofNS work schedules (at home vs. outside home) and its
potential benefit or detriment to child wellbeing. Parents working NS schedules at home may
be able to adjust hours to suit their family needs. Rapoport and Bourdais (2008) have shown
that working at home in general is associated with more time devoted to household chores for
mothers and more time for social activities and family meals for fathers. Future research
should investigate whether the effects ofNS schedules worked at home are different from
those worked elsewhere. Better specification ofNS schedules also requires a focus on the
family as the unit of analysis, considering joint work scheduling patterns in dual-earner
families. The degree to which the work schedules of parents in dual-earner families overlap
also has important implications for parental relationships, the division of household labour,
and parental participation in children's activities (Barnett, 2006; Staines & Pleck, 1983), all of
which may influence child outcomes.
Attention to a Wider Range of Moderating and Mediating Factors
Fourteen of the 23 studies reviewed examined a range of moderating or mediating
factors that were likely to play a role in the association between NS work schedules and child
development. There was, however, a general lack of information on the child's temperament,
parental marital satisfaction, levels of actual and perceived social support, and parents' job
quality. These factors have been shown to influence child development (Brooks-Gunn, Han,
35
& Waldfogel, 2010; Han & Waldfogel, 2007; Strazdins, Shipley, Clements, Obrien, &
Broom, 2010). Strazdins and colleagues (2010) reveal that when parents hold poor-quality
jobs their children show more emotional and behavioral difficulties, independent of income,
parent education, family structure, and work hours. Similarly, job characteristics and job
quality associated with certain types ofNS schedules may be an important confounder or
moderator. For example, the effects ofNS work schedules may be exacerbated by stressful
work conditions, such as long hours, lack of support from coworkers and supervisors, and
pressures for meeting deadlines. It is critical that future research adequately examines the
role these factors may play in mediating or moderating the relationship between NS
schedules and various domains of child development.
Further, whereas most of the reviewed studies adjusted for family structure and
income as confounders, relatively few examined how the relationship between NS schedules
and child outcomes may differ by these contextual factors. It is important to examine factors
that may modify the effect of working NS schedules on child development, such as those
based on SES (Repetti, 2005) and other characteristics of the family and the child. Families
are complex and diverse with different capacities for responding to the challenges of
combining work and family. Families with more resources (e.g., both-parent and high income
families) are either less affected (Han, 2008; Han & Waldfogel, 2007; Strazdins et al., 2004,
2006) or unaffected by NS work schedules (Dockery et al., 2009; Morrissey et al., 2011).
Some small scale studies linking NS work schedules with family processes (Barnett &
Gareis, 2007; Davis et al., 2006) suggest that family with more resources can benefit from
mothers' NS work schedules in terms of fathers' participation in parenting. It is thus important
for future research and interventions to identify and target subgroups of children from less
advantaged families, particularly those who have low levels of multiple developmental
resources (e.g., parental SES, time, psychological and physical health).
36
More Sophisticated Analytical Approaches
Causality and selection bias have always been a concern in social science research.
Increasingly, studies use longitudinal datasets to handle temporal issues in linking parental
work schedules with children's well-being. Longitudinal data, however, do not always enable
researchers to conclusively answer the fundamental question of causality. In the absence of
experimental data, some existing studies have used more sophisticated statistical approaches
to address this issue. For example, Han (2008) used a child fixed effects model to tackle the
issue of unobserved heterogeneity. Other studies have used propensity score matching (Han
et al., 2010) to address selection bias and causality. These statistical tools allow researchers to
compare outcomes for children of parents who worked NS and the children of parents who
did not work such schedules, but had a similar predicted propensity to do so. In this way,
these two groups are comparable so we can minimize the possibility that observed
associations between NS work schedules and child outcomes are attributable to selection bias
(see discussion in Hill, 2008). As more longitudinal data and sophisticated statistical
techniques become available, future studies need to tackle the issue of causality.
Implications for Practice and Policy
We envision a number of ways in which the government and society as a whole can
intervene to prevent or buffer the negative effects ofNS work schedules on children and
families through policy initiatives, where such impact exists. None of the reviewed studies
examined indicators of broader influence outside the home, such as the neighborhood,
community resources (e.g., the accessibility and cost of child care facilities, school, beforeand after-school care for school age children, and public transportation), and work place
policy initiatives. These factors can potentially mitigate the negative association between NS
37
work schedules and child development. For example, greater support at the workplace for
fathers to increase their levels of involvement in child care, and greater quality of father
involvement in household work generally, will come a long way to help families cope with
their daily stress due toNS work schedules. This will, in turn, enhance family and child wellbeing. School also has an important role to play, such as in the provision of healthy breakfast
and lunch at school cafeterias, and greater social and emotional support and intellectual
stimulation targeting children whose parents work NS schedule and may have a reduced
capacity to adequately provide their children with these healthy developmental inputs.
Further, the availability of before- and after-school care and child care for young children
during NS work hours can reduce the stress on parents who work NS schedules. As also
noted by Barnett (2006), the availability of medical appointments on weekends and public
transportation outside normal business hours can assist parents working NS schedules to cope
with demands from work and family. In the absence of such community resources, parents
with NS work schedules may resort to unreliable options (Barnett, 2006). Finally, given
evidence that children living in low-income families are more vulnerable, ensuring adequate
pay and/or supplements paid for NS schedules is another intervention option for industrial
relations and regulatory efforts.
The trend towards the 24/7 economy is unlikely to reverse in the future, and the
evidence to date suggests that some aspects of children's development is shaped by the
timing of their parents work. We are fully aware of the complexity of the ways in which
parental market work affects children's health and development. In spite of the best efforts
made by scholars to capture such complexity, existing research may still barely do justice to
the influences (positive and negative) at play, and the challenges and difficulties confronting
working parents and their children. Possibly, mixed methods may enable researchers to better
understand the everyday experiences of today's families and how these experiences interact
38
with parentallabor market involvement to influence children's development. In many
respects the field is yet to mature, and the next real task is for research and policy to do
justice to the complex relationship between parental NS work schedules and children's health
and development.
39
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Appendix
FIGURE 1. Theoretical Background: Adapted from Bioecological Theory (Bronfenbrenner, 2005) and
Conceptual Resource Framework (Brooks-Gunn et al.,1995)
Mediators
Structural
Factors
Technological
change
Globalization
Labor market
deregulation
A
Nonstandard
(NS) Work
Schedules
Weekend
Evenings
Nights
Irregular shifts
Split shifts
Family Resources
Parent health
Time for children
Income
Human capital
Psychological capital
Social capital
Family Processes
Parenting
Parent-child relationship
Home environment
B
Moderators
Child age
Child gender
Parent gender
Family structure
Family income
Reason for NS
work schedules
Child Development
Mental health and
behavioral problems
Cognitive capability
Health
Appendix
FIGURE 2. Summary of the Literature Search Process
Records identified through
database searching (n = 364)
Additional records identified through
other sources (n = 3)
!
I
!
Records after duplicates removed (n = 241)
I
Records excluded for
not meeting inclusion
criteria (n = 217)
0
0
0
Full-text articles assessed for
eligibility (n = 24)
Studies included in
comprehensive review
(n = 23)
r------+
adult health and wellbeing (n =94)
family process
outcomes (n =32)
other (n
=91)
Full-text articles
excluded after initial
assessment
(n = 1)
Appendix
Table 1. Summary ofReviewed Studies (N= 22)
Study
Sample and
Age
Design
Definition of
Child Outcome
Confounders and
Nonstandard (NS)
Measures
Covariates (C)a I
Results/Effect Size
Quality
Ratingc
Moderators (Mo)/
Work
Mediators (Me)/ Analysis
Techniques_(AT)
Mental health
an et al.,
2010
US: NLSY-CS
Birth
Mother and father:
Risky behaviors at age
C- = MIN, family income,
Full sample (all ages)
Five cohorts of
to age
# of years parent
13--14:
welfare, maternal
-Indirect effect of mothers'# of years of night shift (via time
children born
13/14
worked evening
Ever smoked
occupation, birthweight,
spent with children) on smoking (r.. = -.096**), drinking (r.. =-
1982-1991
years
(2pm-midnight), night
Ever drunk alcohol
smoking & alcohol
.081 **) and drug use (r.. = -.095**)
(N = 4,200)A
(9pm--8am), or
Ever used illicit drugs
consumption during
-Indirect effect of mothers'# of years of night shift (via home
Longitudinal
irregular shift (other
Number of delinquent
pregnancy
environment) on drinking (r.. = -.114***), delinquency (r.. =-
NS types) from birth
behaviors
Me = Child reported: time
.082***), and sex (r.. = -.145***)
to age 11/12.
Ever had sex
together, maternal &
-Indirect effect of mothers'# of years and fathers'# of years
Variables also created
Child_reported
paternal closeness,
irregular shift (via parental knowledge) on smoking (r.. = -
by developmental
parental knowledge,
.088***), drinking (r.. = - .114***), and delinquency (r.. = - .077***)
stage (<5, 5-10, 11-
HOME score
- Direct effect of father# of years irregular shifts on drinking (r.. =
12)
Mo = Child gender,
.080**)
income-to-needs ratio,
Strength & nature of effects varied by developmental stage at
maternal occupation,
which NS work occurred
family structure.
Subgroup analysis showed effects of mothers' night shift
AT= SEM/PSM
stronger among boys, low-income families, when nonprofessional and when a sole parent for majority of time
5
Daniel et
US: NICHD-
6-36
Mother:
Behavioral problems
C = MIN, poverty level,
Effect of mothers' NS schedule (without mediators/ with
al., 2009
SECC
month
Began NS work
(CBCL) at 24 & 36
weeks of maternity leave,
mediators) on Internalizing if
(N = 1,364
(evening, night or
months:
job flexibility, location
-Began NS in 1st yr (24 months): ES = 0.02/-0.04
children born in
variable) in 1st year,
Internalizing T-score
Mo = Child temperament
-Began NS after 1st yr (24 months): ES = --0.13/--0.12
1991 and
or began after 1st
Externalizing T-score
Me = Maternal depression
-Began NS in 1st yr (36 months): ES = 0.24**/ 0.20*
mothers are FT
year vs. only standard
Mother_reported
and sensitivity.
-Began NS after 1st yr (36 months): ES = 0.18/0.16
AT= OLS
Externalizing if
by 6 months)}\
4
-Began NS in 1st yr (24 months): ES = 0.31**/ 0.24*
Longitudinal
-Began NS after 1st yr (24 months): ES = 0.03/0.08
- Began NS in 1st yr (36 months): ES = 0.21 *I 0.19*
-Began NS after 1st yr (36 months): ES = 0.15/0.13
Interactions significant at p < .10 indicating NS schedules had
greater effects on internalizing (24 & 36 months) and
externalizing (24 months)if mother began NS work in the 1st year
of the child's life & child had difficult temperament
Han, 2008
US: NLSY-CS
4-10
Mother & father:
Behavioral problems
C = MIN
All families:
children born
years
NS (6pm- 6am) vs.
(BPI):
Mo =Years lived with
Effect of mothers'# of years NS shift on BP I: ES = 0.03*
1982-1991 of
standard shift (# of
Total score
couple or sole parent,
-Years NS & always single mother family: ES = 0.09**
mothers who
years)
Mother reported
average family income,
-Years NS & bottom 3rd of income distribution: ES = 0.07**
had ever worked
mother's occupation-# of
- Years NS & years cashier/service occupation: ES = 0.01*
(N = 12,207)A
years, average work hours
- Years NS & average hour
Longitudinal
AT= Child FEM
s are FT (>35hrs): ES = 0.1 0***
Two-parent families:
- Mothers'/fathers' # of years NS shift: ES = 0.03/ ES = 0.01
4
-Years mother NS & average hours are FT: ES = 0.1 0***
- Years father NS & average hours are FT: ES = 0.1 0***
Rosenbaum
US: ECLSBC
9-24
Couple:
Behavioral problems
C- MIN, preterm,
Effect of parental NS shift (without/with mediators) on behavioral
& Morett,
(N = 1,650)
month
At least one parent
(ITSC) at 24 months
birthweight, childcare type,
problems at 24 months:
1009
Children born in
works NS shift;
Mother_reported.
job benefits, more than 1
- Either/ both parents work NS shift: ES = 0.19***/ ES = 0.14*
2001 & in DE
6-category variable -
job, child ITSC at birth
- Father day, mother evening/night:
families at
day (6am--6pm)/
Mo = Parent gender
-Father day, mother irregular: ES = 0.23**/ ES = 0.18*
baseline (9
evening (2pm-
Me = Father-child
-Father evening/night, mother day: ES = 0.32**/ ES = 0.15
months)}\
midnight)/night (9pm-
interaction, marital quality,
- Father irregular, mother day: ES = -0.15/ ES = --0.22*
Longitudinal
8am )/rotating/split/
shared dinners, self-rated
- Both evening/night/irregular: ES = 0.06/ ES = -0.21
other
health, depression
4
ES = 0.35***/ ES = 0.34***
AT= OLS
Dockery et
Australia: HILDA
15--20
Either mother or
SF36 mental
C = MIN, family prosperity,
Effect of either parent working NS hours (without/with mediators)
al., 2009
waves 1-4,
years
father works
component score (M=
long-term disability.
on SF36 mental health score:
2001-2004
NS hours in couple
50, SO= 10).
Mo = Family structure,
-All families: ES = -0.08*/ ES = --0.08*
(unbalanced
families; one parent in
Child_reported
work hours
-Lone parent: ES = --0.19*/ ES = --0.19*
panel: N = 3,429
lone parent families
Me = Time with children,
-Two-parent: ES = -0.06/ ES = --0.07
observations,
(all types including
parental mental health.
1 ,691 youth,
weekend) vs.
AT= OLS
1,197 houses)A
standard
3
Cross-sectional
Dunifon et
US: WES, Ll
2-15
Mother mostly
Behavioral problems
C = MIN, average hourly
Total sample (results from OLS)
tl., 2005
women
years
NS i.e., evening or
(BPI) at wave 4_(aged
wage, irregular hours,
Effect of mothers' NS shift on behavioral problems:
mixed day/evening (at
5-15):
lengthy commute, marital
- NS shift at W1 & internalizing: ES = -0.07
(N = 372) from
3
cash assistance
1 wave only, or at 2 or
Internalizing
status; mother's self-rated
- NS shift at W1 & externalizing: ES = --0.07
rolls, 1997-2002
more waves) vs.
Externalizing
health, mental health,
- NS shift at W1 & positive behavior: ES = --0.06
(4waves,
mostly standard shift
Positive behavior
learning disability, stress,
- NS shift at W2+ & internalizing: ES = 0.12
Mother_reported
domestic violence
- NS shift at W2+ & externalizing: ES = 0.04
employed in at
Mo = Child age/ gender,
- NS shift at W2+ & positive: ES = -0.08
least one wave
no of other adults in house
Longitudinal
AT= OLS/ FEM
No significant interactions
women
Han &
US: NSLY-CS
Birth
Mother & father:
Adolescent
C- MIN, welfare reliance,
-Indirect effect of maternal# of years night shift and paternal#
Miller, 2009
Five cohorts of
to age
Standard (6am-6pm),
Depression Scale at
family income, marital
of years evening shift (via home environment) on depression (r..
children born
13/14
evening (2pm-
age 13--14
status, birthweight,
= -.036***)
1982-1991
years
midnight), night
Child_reported
smoking or drinking in
-Indirect effect of paternal# of years evening shift (via paternal
(N = 4,200)1\
(9pm--8am), irregular.
pregnancy, occupation
closeness) on depression (r.. = -.096***)
Longitudinal
Measured as # of
Me = Time with parents,
-Indirect effect of maternal# of years irregular shift & paternal#
years from birth to
parent-adolescent
of years irregular shifts (via mothers' knowledge of whereabouts
age 11/12
relationship, monitoring,
on depression (r.. = -.070***)
3
HOME score, frequency of
meals, TV.
AT= SEM
Han &
US: NLSY-CS, 8
1G-14
Mother & father:
Risk-taking behavior:
C = MIN, marital status,
Two-parent families
Waldfogel,
waves 1988-
years
6 category:
Substance abuse
birthweight, mother's
Effect of mothers' evening shift (unmediated/mediated) on:
2007
2002
Standard (8am-6pm),
Disobedience
cognitive ability, income
-Criminal behavior: OR= 1.48 (0.26)*/ OR= 1.38 (0.26)
(N = 12,207)A
Evening (2pm-12),
Criminal behavior
Mo = Family type.
Single-mother families
Cross-sectional
night (9pm-8am),
School-related trouble
Me= Parental monitoring,
Effect of mothers' rotating shift (unmediated/mediated) on:
rotating, irregular
Child_reported
child-parent closeness.
- Disobedience: OR= 1. 77 (0.41 )*I OR= 1.63 (0.38)*
3
AT= LOGR
-Criminal behavior: OR= 1.57 (0.29)* I OR= 1.49 (0.28)*
-School trouble: OR= 1.74 (0.33)** I OR= 1.59 (0.31)*
Hsueh &
US: Ll from
5-16
PCG (mother): 4-
Behavioral problems
C- MIN, parental gender,
Effect of mothers' NS shift (without mediators) on:
Yoshikawa,
Milwaukee,
years
category variable -
(BPI) at 2-year (age
access to car, income,
Parent-reported
2007
Wisconsin New
Fixed NS shift (at
5-12) & 5-year (age
receipt of AFDC
-Internalizing (2-year): 13 = -.1 0/13 = -.13* (fixed /variable NS
Hope Project
least 50% hours
6-16)
Me = Parental stress,
shift)
1994-1995
outside 8am-4pm,
Internalizing
perceived time pressure,
-Internalizing (5-year): 13 = .09/ 13 = -.05
(N = 486
incl. weekend);
Externalizing
regularity of family
-Externalizing (2-year): 13 = .01/ 13 = .02
parents, 529
variable NS; variable
School engagement
mealtime.
- Externalizing (5-year): 13 = -.03/ 13 = .02
children with
standard vs. fixed
School performance.
AT= OLS
Teacher-reported
valid data)
standard at 2-year
Teacher and parent
Longitudinal
followup
reported.
-Internalizing (2-year): 13 = -.071 13 = .02
Adjusted for 2-year
-Internalizing (5-year): 13 = -.02/ 13 = -.00
outcomes at 5--year
- Externalizing (2-year): 13 = -.05/ 13 = .15*
followup
- Externalizing (5-year): 13 = -.05/ 13 = .01
Strazdins et
Canada: NLSCY
2-11
Mother or father or
Social & emotional
C = MIN, child care use
Effect of parental NS shift (without/with mediators) on social and
al., 2006
1996--1997
years
both NS (any incl.
wellbeing derived from
Mo =Child age (2-4/5-
emotional wellbeing:
(N = 4,306 DE
weekends) vs. both
CBCL (M= 0, SO= 1).
11), SES (derived
- Father NS (all children):
families, 6,156
standard
PCG_reported
composite)
- Mother NS (all children): 13 = .14**/13 = .08*
Me= Family functioning,
- Both NS (all children): 13 = .14** /13 = .07*
parental depressive
- Father NS (1st SES quartile, all children): 13 = .16/13 = .07
symptoms, hostile or
- Mother NS (1st SES quartile, all children): 13 = .18/13 = .09
ineffective parenting
-Both NS (1st SES quartile, all children): 13 = .19*/13 = .07
AT= Linear mixed model
- Father NS (pre-school children): 13 = .25**/13 = .18**
with household random
-Mother NS (pre-school children): 13 = .20**/13 = .12*
children)
1\
Cross-sectional
3
13 = . 16**/13 = . 11 **
3
effect
-Both NS (pre-school children): 13 = .22**/13 = .14**
Gassman-
US: Children of
Pre
Mother:
Child behavior
C -MIN, teenage parent,
Effect of each increasing hour of mothers' night work on:
Pines, 2011
Ll working
school
Based on daily diaries
Externalizing
living with grandparent;
-Externalizing: ES = 0.04
mothers from
age
-night (6pm-6am) or
Internalizing
other daily level covariates
-Internalizing: ES = 0.04
preschool at
weekend vs. daytime
Positive behavior
e.g., whether child was
- Positive behaviors: ES = -0.06*
four Head Start
(8am-6pm), (#of
Mother-child
sick that day, care by
Centres (N = 61
hours of each)
interactions- 5
father.
Interaction significant at p < .05 indicated that the effect of# of
mothers, 724
subscales
Mo =weekend
hours worked at night on the weekend reduces positive behavior
person-days)
Maternal mood
AT= MLM
more so than # of hours worked at night on a weekday
Cross-sectional
Mother_reported
I
Han, 2006
US: NSAF,
6--17
Mother:
Behavioral problems
C- MIN, childcare type
Effect of mothers' NS schedule on behavioral problems at:
children of
years
NS (6am-6pm) vs.
(BPI)
Mo =Child age (6-11/12-
- 6-11 yrs (1997/1999): ES = --0.06/0.01
standard
Extra-curricular
17), marital status and
-12-17 yrs (1997/1999): ES = -0.03/0.05
(N = 20,823 in
activities
work hours, family poverty
1997;
School engagement
and welfare status,
N = 21,730 in
MKA (mostly mother)
parenting stress and
1999)
reported
mental health.
working mothers
1\
2
AT= OLS
Cross-sectional
US: 1999,
2-4
Mother: "regular"
Behavioral problems,
C- MIN, city, welfare,
Effect of mothers' NS schedule (without/with mediating factors)
Bog en,
206 Ll children
years
NS (all types including
CBCL (M= 0, SO= 1):
income, health insurance,
on:
2007
from Welfare,
weekend) vs.
Internalizing
depressive symptoms &
-Internalizing: 13 = 0.47*1 13 = 0.32
Children &
standard
Externalizing
social support, birthweight
-Externalizing: 13 = 0.55**/ 13 = 0.37*
Families: A
Positive behavior
or preterm
-Positive behavior: ES = --0.36**/ ES = -0.27*
Three City
Mother_reported
Mo = Child gender,
oshi &
2
2
Study
presence of biological
Interactions significant at p <. 10 indicate the effect of mothers'
Cross-sectional
father, & other adults.
NS schedules on internalizing was less if other adults were in the
Me = Parenting stress.
household; and effect on externalizing was less if child was a
AT= OLS
boy
Strazdins et
Canada: NLSCY
2-11
Mother/father/both
At least one emotional
C = MIN, child care use
Effect of NS schedule on child emotional or behavioral difficulty:
tl., 2004
1996-97
years
NS (any incl.
or behavioral difficulty
Mo = Child age (2-4/5-
- Father NS (all ages): OR= 1.29 (1.04-1.60)*
(N = 4,433 DE
weekends) vs. both
(14%)
11),SES(derived
- Mother NS (all ages): OR= 1.43 (1.13-1.81 )**
families, 6361
standard - usually
PCG_reported
composite measure from
- Both NS (all ages):
children)
worked in past 12
education, income and
- Father NS (1st SES quartile, all ages): OR= 1.35 (0.83-2.19)
months
occupation)
- Mother NS (1st SES quartile, all ages): OR= 1.67 (1.02-2. 75)*
AT= LOGR
- Both NS (1st SES quartile, all ages): OR= 1.62 (1.03-2.54)*
1\
Cross-sectional
2
OR= 1.40 (1.12-1. 73)**
-Father NS (pre-school children): OR= 1.89 (1.30-2.74)***
- Mother NS (pre-school children): OR= 1.65 (1.09-2.48)*
- Both NS (pre-school children): OR= 1.81 (1.24-2.66)**
Barton et
UK: (N= 190
8-11
Father:
C =Age
Effect of father working a regular shift on:
al., 1998
children of
years
Shift or day
CDI total score and
Mo = Child gender
-Perceived academic competence (girls only): F (1 ,80) = 4.40*;
employed
subscales
AT= MANOVA
and discrepancy between perceived and ideal levels of
fathers-
Child_reported
(SPPC) subscales
competence (girls only) F (1, 76) = 4.99 *
manual/semi-
Girls had more symptoms than boys when fathers worked shifts
skilled workers)
of depression (total score): F(1 ,76) = 4.93*; negative mood: F
Cross-sectional
1,87)= 4.42*; interpersonal problems: F (1, 87) = 8.33**; and
anhedonia: F (1, 87) = 4.30*
Cognitive Ability (see also Han, 2006 and Hsueh & Yoshikawa, 2007 for outcomes related to school engagement, school performance and involvement in extracurricular activity)
Odom et al.,
US: N- 231
2-3 yrs
Mother:
Child expressive
C - Child age, income/
Effect of mother working a NS schedule without (with) mediators
0
2013
children of
NS (fixed evening,
language outcomes:
needs ratio, work hours,
on:
employed
fixed night, rotating
NOW@ 24 months
maternal education, formal
-NOW at 24 months: 13 = -.16*/13 = -.12
African
shift or irregular) vs
PLS @ 36 months
child care
-PLS at 36 months: 13 = -.12*/13 = -.06
American
standard (most hours
Me= maternal positive
mothers born in
8am-5pm) at 24
engagement, negative
2002 in low-
months
work-family spillover
AT= OLS
wealth rural
households from
The Family Life
Project
Longitudinal
Han & Fox,
US: NLSY-CS
Birth
Mother & father:
PIAT Reading and
C = MIN, marital status,
Mothers
1011
(N = 7, 105).
up to
Standard (6am-6pm);
Math (level and
family income, welfare,
Effect of# of years night shift (without/with mediators) on:
Six cohorts of
13-14
Fixed evening (2pm-
trajectory) from ages 5
occupation
-Reading level: ES =- 0.02*/- 0.02*
children born
years
9pm); Fixed night
to 14).
Me = Child reported: time
- Reading trajectory: ES = 0.01
1982-1993 who
(9pm-6am); Variable
together, maternal &
- Math level: ES = 0.02/0.01
have been
(other schedule).
paternal closeness, parent
- Math trajectory: ES = -0.05**
missing events, parental
Effect of# of years evening shift (without/with mediators) on:
followed for
13-14 year
# of years worked
knowledge, HOME score,
-Reading level: ES = -0.01/-0.01
period)
evening, night or
shared meals, after-school
- Reading trajectory: ES = 0.00
variable shifts
activities
- Math level: ES = 0.03**/ 0.02
AT= Multilevel GCM
- Math trajectory: ES = -0.04**
A
Longitudinal
Effect of# of years variable shift (without/with mediators) on:
- Reading level: ES = 0.02**/0.02**
4
- Reading trajectory: ES
- Math level: ES
=-0.02*
=0.02**/0.01
- Math trajectory: ES
=-0.02
Fathers
Effect of# of years night shift (without/with mediators) on:
-Reading level: ES =- 0.04**/0.01
- Math level: ES
=0.03*/0.03*
Effect of# of years evening shift (without/with mediators) on:
- Reading level: ES
- Math level: ES
=-0.02/-0.02
=-0.02/-0.03*
(Note that there was not association between fathers work
schedule and trajectories)
Han, 2005
US: NICHD-
0-3
Mother:
BMDI at 15 & 24
C -MIN, maternal
Effect of mother beginning NS schedule in the child's 1st year
SECC (N= 900
years
NS (combined
months
cognitive ability, family
and continuing to 3rd year (without/with mediators) on:
children whose
evening 3pm-
BSR at 36 months
income, poverty,
- Bayley MDI (15 months): ES
=--0.20*/ ES =--0.13
mothers had
midnight/ night
Reynell Verbal
depression at one month
- Bayley MDI (24 months): ES
=--0.21**/ ES =--0.12
worked in the
(11 pm-7am)/ variable
comprehension &
Me
first 3 years)
hours) vs. standard.
Expressive language
employment, maternal
- Reynell verbal (36 months): ES
Children born in
Measured seven
at 36 months
depression, home
- Reynell expressive (36 months): ES
1991A
combinations of onset
Mother_reported.
environment, mother's
Longitudinal
and duration
=Amount of maternal
sensitivity, childcare type
and quality
AT= OLS
- Bracken school readiness (36 months): ES
=--0.02/ ES =0.03
=--0.30***/ ES =-0.21 *
=--0.20*/ ES =-0.15
(See paper for results for other schedule onset and duration)
3
eymann,
US: NLSY-CS
School
Parents:
Mathematical ability
C =_Child gender, parental
Effect of parent's NS work schedules on:
000 (pp
199G-1996
aged
Evening (6-9pm)
(PIAT); Vocabulary
education, marital status,
- Low maths achievement- bottom quartile on PIAT (#of hours
Night shift
Reading; Repeating a
work hours, family income
worked by parent in evening): OR= 1.17, p < 0.05
working
year at school;
AT= OLS
-School suspension (night shift): OR= 2.72, p < .01
parents)A
School suspension
55-56)
(N = 4,689
Other OLS results N/A
Cross-sectional
Body Mass Index (BMI)
Champion
Australia:
9
Mother and father
Overweight or obese
C = MIN, time child
Effect of mother's NS work schedule on:
et al., 2012
Generation 1
years
(partner living in the
based on age and
spends in front of a TV,
- Overweight/obese: OR= 1.26, p > .05
Study (N = 434
home):
gender standardised
computer or game system
Effect of father's NS work schedule on:
children of
Standard (9am -
BMI (International
AT= LOGR
- Overweight/obese: OR= 1.97, p < .05
mothers living in
6pm); NS ('always' or
Obesity Taskforce)
Adelaide 2008-
'often' working shifts,
- Overweight/obese: OR= 2.26, p > .05
2010)
after 6pm or overnight
(compared with standard work schedule)
1\
2
Effect of both parents working a NS work schedule on:
or weekend); Not
Cross-sectional
employed.
Joint parental work
schedules
Morrissey et
US: NICHD
8-12
Mother:
Age and gender
C- MIN, birthweight, child
Effect (without mediators) of mothers' NS schedule on BMI (in
al., 2011
SECC (N= 990
years
NS (7pm-8am) vs.
standardised BMI
grade, income
child FEM- authors preferred model): ES = 0.20
children in 3rd,
standard at each
Me = TV time, physical
5th and 6th
grade/ number of data
activity, HOME
Effect (without mediators) of# of periods mother worked NS
grades-
points with NS
environment, parental
schedule on BMI (in child FEM): ES = 0.02
complete data
schedules from 3
supervision &engagement,
4
for at least 2
months to 2nd grade
mother depression
grades). Born in
- max 19)
Mo = gender, grade,
1991/\
maternal education
Longitudinal
AT= REM I Child FEM
No significant moderated effects
Miller&
US: NLSY-CS
13--14
# of years mother
Continuous BMI
C = MIN, birthweight,
Effect of# of years mother worked NS shift on:
Han, 2008
Five cohorts of
years
worked
Risk of overweight
mother's cognitive ability,
BMI continuous if
children born
NS (evening 2pm-
(cutoff >85th
income at baseline, years
-full sample: ES = 0.10*
1982-1991
midnight/night 9pm-
percentile of BMI)
in poverty, frequency of
-ever I never a single parent: ES = 0.11/ ES = 0.08
(N = 2,353
8am/split/ other) vs.
Child_reported
TV, shared dinners;
- income quartiles 1 to 4: ES = 0.22; 0.27*; 0.04; 0.07
children of
standard (6am-6pm)
mother's BMI
BMI >85th percentile if
mothers who
Mo = Family income,
-full sample: OR= 1.34(1.07-1.68)*
ever worked)/\
whether child had ever
-ever I never a single parent: OR= 1.25(0.91-1. 71 )/OR=
Longitudinal
lived with a single mother.
1.43(1.03-1.99)*
AT= OLS/LOGR
- income quartiles 1 to 4: OR= 1.66 (0.97-2.85);
1.97(1.20-3.26)**; 1.05(0.68-1.60); 1.18(0.77-1.83)
Sleep Patterns
Radosevic-
Croatia:
11-18
Couple:
Sleep patterns:
C = child gender, type of
Effect of having one shiftworking parent on:
rrek&
(N_=_2,363
years
Both day, one
Child reported
school (elementary/high)
- usual waketime of high school students when attending school
students in DE
nonstandard, both
Usual bedtime
AT= MANOVA
in the morning (earlier): F (2, 1,360)= 4.97**
families 2001-
nonstandard
Usual waketime
MO = child gender
Effect of having both shiftworking parents on:
02)/\
Child reported
Calculated
-sleep duration of high school students attending school in the
Sleep duration
morning (shorter): F (2, 1,360)= 5.24**
Bedtime delay and
- bedtime on the weekend (later): F (2, 1 ,360) = 7.85**
sleep extension
- See paper for more results on bedtime delay and sleep
oscec,
2004
Cross-sectional
3
extension on weekends.
+p< 0.10 *p < .05, **p < .01' ***p < .001
Note. b = unstandardized coefficient; !3 =standardized coefficient; BMDI = AFDC =Aid to Families with Dependent Children; Bayley Mental Development Index; BMI =Body Mass Index; BPI =
Behavioral Problems Index; BSR = Bracken School Readiness; CBCL = Child Behavior Checklist; CDI = Children's Depression Inventory; DE = dual earner; ECLSBC = Early Childhood Longitudinal
Survey Birth Cohort; ES =Effect Size calculated by authors as b/SOy; FEM = Fixed Effects Model; FT= full-time; GCM =Growth Curve Modelling; HI LOA= Household, Income and Labour
Dynamics in Australia; HOME= Home Observation Measurement of the Environment; ITSC =Infant Toddler Symptom Checklist; Ll =low income; LOGR =Logistic Regression; MANOVA =
Multivariate Analysis of Variance; M = mean; MKA = Most Knowledgeable Adult; MLM = Multilevel Modelling; N/A = not available; NOW= Number of different words; NICHD-SECC = National
Institute of Child Health and Human Development Study of Early Child Care; NLSCY = National Longitudinal Study of Children and Youth; NLSY-CS = National Longitudinal Study of Youth- Child
Supplement; NSAF = National Survey of American Families; OR= Odds Ratio; OLS =Ordinary Least Squares regression; PCG =Primary Caregiver; PIAT = Peabody Individual Achievement Test;
PLS = Preschool Language Scale; PSM = Propensity Score Matching; SO= standard deviation; REM = Random Effects Model; SEM = Structural Equation Modelling; SES =socioeconomic status;
SF36 =Short Form 36; SPPC =Self-perception profile for children; UK =United Kingdom; US= United States; WES =Women's Employment Study; W1 =one wave; W2+ =two or more waves;
AStudy is representative of a population or subpopulation.
aM IN= minimum set of sociodemographic confounders and covariates included in the analysis i.e., child gender, child age (or developmental stage), number of children in household (or presence of
siblings/birth order), family structure (couple/lone, presence of a non-biological parent, marital status), parental age (at least of mother), parental work hours (at least of mother, and at least FT/PT status),
parental education, race/ethnicity (of parent or child).
bWhere possible all results for the study have been provided regardless of statistical significance. When there are too many results to report in the table, only those significant at p < .05 have been
presented (e.g., for SEM models).
cstudy quality rating is from 0-5 indicating the number of criterion met by the study as determined by the authors: (1) sample is representative of population or subpopulation, (2) study design is
longitudinal, (3) a minimum set of sociodemographic confounders have been considered, (4) analytical methods have been used to address selection bias, and, (5) the study has considered at least one
moderator and one mediator.